Specifications for a successful analysis Standard Tool 1 Description of WimTube... 2 2 Specifications for the input files... 2 2.1 Description... 2 2.2 Valid Formats... 2 2.3 Microscopy Techniques... 2 2.4 Image Quality Characteristics... 2 3 Results description... 3 3.1 Result Images... 3 3.2 Result Data... 4 3.3 Result Data Summary... 6 Wimasis GmbH Karlstraße 55 D-80333 Munich (Germany) CEO Carlos Urquízar Page 1 of 5
1 Description of WimTube WimTube is the image analysis solution to quantitatively evaluate the generation of new vessels during the tube formation assay. It helps monitor the angiogenic behavior of cells over time and enables the estimation of time dependent effects in the neovascularization in tube formation. WimTube is specially engineered to work with phase contrast, bright field and fluorescence images, although its flexibility makes it suitable for other imaging modalities, covering the broad range of microscopy techniques used to monitor the process of tube formation. 2 Specifications for the input files 2.1 Description WimTube input files are individual images where cells and tubular structures are shown over a clear and even background. 2.2 Valid Formats WimTube image analysis module accepts the following file formats: Images jpg png tif bmp jpeg gif tiff 2.3 Microscopy Techniques WimTube is specially designed to analyze images of the following microscopy techniques and will reach its best performance with them: Bright-field images Phase contrast images Fluorescence images Example of a bright-field image (A), a phase contrast image (B) and a fluorescence image (C) Wimasis GmbH Karlstraße 55 D-80333 Munich (Germany) CEO Carlos Urquízar Page 2 of 5
Nevertheless, WimTube is engineered with flexibility to adapt to all kind of images, so it accepts images of the whole range of microscopy techniques used in tube formation assay with the aim to provide every researcher with the automated analysis that best fits his needs. 2.4 Image Quality Characteristics In order to get the best results from WimTube, it is recommended to upload input images that fulfill the following quality requirements: Avoid visible containers (e.g. wells, plates, chambers, etc.). The edge of these objects can be confusing and lead to detect them as false tubes. No additional information visible (e.g. scale bars, time stamp, etc.). Some microscopes draw additional information on the image, like a scale bar. This should be avoided because these extra features distort the appearance of the image, resulting in a loss of information for the image analysis. Be focused. Images should be properly focused in order to allow tubes to be viewed with the best contrast achievable and make the distinction between them and the background as neat as possible. No artifacts, noise or debris. The background of the image should be clean and low on debris and artifacts. The prevention of air bubbles, dead cells and other visible objects appearing in the background will help the readouts to be more precise and the data to be the most accurate. Homogeneous illumination. Achieving homogenous lighting conditions throughout the entire image will assure better results. Please, avoid images with bright spots in the center and dark spots in the corners. Moderated cell density. A medium cell density on the image will favor a proper detection of the background. Good resolution. Very low resolution images may cause a wrong detection of the tubes and complicate its distinction from the background. Our standard solution only guarantees accurate results when the input images do meet these quality standards. If that is not the case, we cannot assure reliable results of WimTube standard tool, but we will make an adaptation of the standard tool to fit WimTube to your images and provide you with the analysis you need. To get an adaptation for WimTube for free, contact us here: contact@wimasis.com or +49 (0)89 452 44 66 0 3 Results Results will be provided in a zip file that will have the following files within: Result images (one per image uploaded) Result data (one per image uploaded) Wimasis GmbH Karlstraße 55 D-80333 Munich (Germany) CEO Carlos Urquízar Page 3 of 5
Result data summary (one per order) Please, be aware that the parameters described in the following sections are the ones provided by the standard tool. Any other parameter could be added under request. Just contact us and tell us what you need: 3.1 Result Image contact@wimasis.com or +49 (0)89 452 44 66 0 Every input image will produce an output image consisting on the input image with the tubular structure and the other tube formation parameters outlined on it, as shown on the image below. Example of a result image where the tubular structure (blue), tubes (red), branching points (white) and loops ID (yellow) are marked. This image will have the name of the input image followed by _Exp01 and will be saved in jpg format. The parameters appearing on it are: covered area (blue), tubes (red), branching points (white) and loops (numbered in yellow). 3.2 Result Data Every input image will produce an output csv file with the following measurements: General Metrics: Covered Area [%]. It is the percentage of covered area, that is, the percentage of tubular structure in the whole area of the image. It is calculated dividing the total number of pixels of the image by the pixels that belong to the tubular structure. Total Tube Length [px]. The length in pixels of the whole tubular structure. Wimasis GmbH Karlstraße 55 D-80333 Munich (Germany) CEO Carlos Urquízar Page 4 of 5
Total Tubes. It is the number of tubes on the image. A tube is considered to be the part of the tubular structure between two branching points or a branching point and a loose end. Mean Tube Length [px]. Arithmetic mean of the individual tube lengths. Standard Deviation Tube Length [px]. It is the standard deviation of the tube lengths. Total Branching Points. The branching points are parts of the skeleton where three or more tubes converge. Total Loops. A loop is an area of the background enclosed (or almost) by the tubular structure. They are identified by a yellow number on the control image. Mean Loop Area [px]. For each loop, the area (number of pixels) enclosed by it is considered as its area. So, the mean loop area is the arithmetic mean of the area of all the loops. Standard Deviation Loop Area [px]. It is the standard deviation of the area of all the loops. Mean Loop Perimeter [px]. For each loop, the pixels that belong to its edge (pixels that are in contact with the blue tubular structure) are considered its border. The number of pixels of this border is its perimeter and the mean loop perimeter is the arithmetic mean of the perimeter of all loops. Standard Deviation Loop Perimeter [px]. It is the standard deviation of the perimeter of all loops. Total Nets. A net is an isolated region of tubes that contains, at least, one branching point; so, isolated tubes are not considered as nets. Individual Loops Metrics: Loop ID. Yellow number on the control image that identifies each loop. Area [px]. Number of pixels that are enclosed within the corresponding loop. Perimeter [px]. Number of pixels that belong to the corresponding loop border. 3.3 Result Data Summary Every uploaded order produces a csv file that summarizes the measurements contained in all the individual csv results data files of the order. This file will have the name of the order number followed by _Summary. Wimasis GmbH Karlstraße 55 D-80333 Munich (Germany) CEO Carlos Urquízar Page 5 of 5